Deaths

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Total

per 10k

per 1k vaccinations (one or more dose)

Infections

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Total

per 10k

per 1k vaccinations (one or more dose)

About this counter-factual

This counter-factual assumes that no vaccines are available for any countries. The comparison to the baseline can be thought of as the number of deaths averted by the vaccination campaign. As mentioned in the About tab, the values here probably represent a upper estimate.

Theoretically no countries should have negative deaths averted. The few countries that do are countries that received few vaccines and have only seen a increase in deaths due to floating point precision errors when calculating the difference between two identical simulations. These countries have been set to 0.

About

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Background

This flexdashboard displays leaflet maps for a counter-factual-based analysis of the impact of the various COVID-19 vaccines up to 2021-09-09. Various counter-factuals, e.g. no vaccines, distribution based upon country population size etc. are simulated using Imperial College London’s nimue model. All other epidemic parameters for each country are taken from the fits presented here. The simulated counter-factuals are compared to a simulation generated using these fits that represent what occured in reality (this is referred to as the baseline). The maps show the difference in deaths and infections between these two simulations for each country. Additionally, the individual numbers of deaths and infections or vaccines assigned (in the counter-factual) can also be plotted using the icon in the top right hand corner.

Additional maps with adjustments can be plotted by selecting the relevant tab. Per 10k refers to deaths/infections per 10,000 people in the countries populations and per 1k vaccinations is per 1,000 people vaccinated (with at least one dose) in that country in reality.

Limitations

As a warning this method assumes that vaccination campaign have no impact on any non-vaccine interventions (these are represented by changes in the parameter Rt).This could be unreasonable as, for example, if less vaccines are available for a country then they might stay in a stricter lockdown than in they did in reality. This makes the model’s value of Rt higher than it should be, meaning that for the No Vaccines counter-factual the deaths averted should be viewed as an upper estimate the true deaths averted.

This is more complicated for the other counter-factuals since some countries will be receiving more vaccines than they did in reality hence their Rt is likely too low as the country may have reduced their non-vaccine interventions more than they did in reality.

These models are currently fitted using reported deaths and some of the reported cases. Hence this is dependent on the quality of the reported data from each country and is sensitive to under-reporting.

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Figure 1

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Usage

The maps are presented as chloropleths with categorical colouring, a countries exact value can be viewed by hovering over it with your mouse.

The comparison of deaths/infections to the baseline is set up so that positive values mean an increase in deaths/infections under the selected counter-factual and a negative value indicates a decrease. For example in the No Vaccines counter-factual the UK has a value of 370354 (total) deaths as can be seen in figure 1. This indicates that there would have been 370354 more deaths if there had been no vaccines in the UK. It is useful to think of 370354 as the number of deaths averted by the real-life vaccinations.

The map tabs for simulated and baseline deaths just show the total or adjusted death counts and by definition are positive numbers. These are both presented on the same colour scale to make comparisons easier.

The map tab for Vaccinated People (1 or 2 doses) show the number of vaccines assigned to that country in the selected counter-factual. For No Vaccines this is 0. Please note that per 1k vaccinations is the number of vaccinations total (in the baseline) whilst this map plots people vaccinated (in the counter factual).

Some small island nations, e.g. the Maldives, are represented by tiny polygons. The best way to view these is to mouse over them whilst zoomed out.